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VOLUME 210
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医网琴声
www.dnathink.org
September 2002
(ISBN 1-59259-291-0)
MHC Protocols
1. HLA Informatics: Accessing HLA Sequences from Sequence
Databases (288
Robinson, James; Marsh, Steven G. E. KB)
pp. 03-22
2. Accessing HLA Sequencing Data Through the 6ace Database
Horton, Roger; Beck, Stephan (592
pp. 23-42 KB)
3. HLA Typing by Restriction Fragment Length Polymorphism
Analysis
(172
Vaughan, Robet W.
KB)
pp. 45-60
4. PCR-Restriction Fragment Length Polymorphism Typing of
Class I and II Alleles
Vaughan, Robert W.
pp. 61-66
5. PCR-Sequence-Specific Oligonucleotide Probe Typing for
HLA-A, -B, and -DR
(880
Middleton, Derek; Williams, F.
KB)
pp. 67-112
6. HLA-DPA1 and -DPB1 Typing Using the PCR and
Nonradioactive Sequence-Specific Oligonucleotide Probes
Steiner, Lori L.; Moonsamy, Priscilla V.; Bugawan, (456
Teodorica L.; Begovich, Ann B. KB)
pp. 113-142
7. PCR-Sequence-Specific Primer Typing of HLA Class I and
Class II Alleles
(536
Bunce, Mike
KB)
pp. 143-172
8. HLA Typing With Reference Strand-Mediated Conformation
Analysis
Argüello, J. Rafael; Pérez-Rodríguez, Martha; Pay, Andrea; (220
Fisher, Gaby; McWhinnie, Alasdair; Madrigal, J. Alejandro KB)
pp. 173-190
9. Sequencing Protocols for Detection of HLA Class I
Polymorphism
(500
Dunn, Paul P. J.; Cox, Steven T.; Little, Ann-Margaret
KB)
pp. 191-222
10. HLA-E and HLA-G Typing
Martinez-Laso, Jorge; Gomez-Casado, Eduardo; Arnaiz-
(156
Villena, Antonio
KB)
pp. 223-236
11. Typing Alleles of HLA-DM
Teisserenc, Hélène (144
pp. 237-246 KB)
12. Typing Alleles of TAP1 and TAP2
Powis, Stephen H. (148
pp. 249-258 KB)
13. Determining Alleles of the C2 Gene by Southern Blotting
Zhu, Zeng-Bian; Volanakis, John E. (148
pp. 259-268 KB)
14. Complement C4 Protein and DNA Typing Methods
Schneider, Peter M.; Mauff, Gottfried (292
pp. 269-296 KB)
15. Typing of Tumor Necrosis Factor Alleles
Wilson, Anthony Gerard (148
pp. 297-304 KB)
16. Molecular Typing of the MHC Class I Chain-Related Gene
Locus
Collins, R. W. M.; Stephens, Henry A. F.; Vaughan, Robert (216
W. KB)
pp. 305-322
17. HLA Microsatellite Analysis
Carrington, Mary (152
pp. 325-332 KB)
HLA Informatics 3
1
HLA Informatics
Accessing HLA Sequences from Sequence Databases
James Robinson and Steven G. E. Marsh
1. Introduction
Scientists working in the human leukocyte antigen (HLA) field
have access to a number of different informatics resources for the
analysis and interpretation of HLA sequences. Recent advances in
bioinformatics have resulted in an increase in the number of tools
and facilities available for sequence analysis. Researchers can now
utilize these tools to analyze the genomic information within their
own field; in addition, the HLA field also has a number of groups
developing software specifically for this area. Within this chapter,
we will be discussing both the more general tools and the specialist
HLA informatics tools available.
There are a number of different sequence databases available and
the type of database can influence the information retrieved. Data-
bases range from the large international data repositories like the
European Molecular Biology Laboratory Nucleotide Sequence
Database (EMBL), GenBank®, and the DNA Databank of Japan
(DDBJ) through to specialist systems like the ImMunoGeneTics
project IMGT/HLA Database. It is therefore imperative that the user
understands the merits and flaws of the various systems. This
From: Methods in Molecular Biology, vol. 210: MHC Protocols
Edited by: S. H. Powis and Robert W. Vaughan © Humana Press Inc., Totowa, NJ
3
4 Robinson and Marsh
chapter will provide information on the various options available to
the user, to permit an informed decision when selecting a database.
The main databases discussed in this article are the large public
sequence databases, protein structure databases and databases spe-
cializing in the human major histocompatibility complex (MHC).
All of the databases mentioned in this chapter are accessed via
the Internet. The advent of the Internet has revolutionized the dis-
semination of sequence information, allowing scientists from all
over the world to log on and access the many databases that relate to
gene sequences using the World Wide Web (WWW). The uniform
resource locators (URLs) of all the databases discussed will be in-
cluded in Section 6. of this chapter.
2. Generalist Nucleotide Sequence Databases
2.1. EMBL/GenBank/DDBJ
The generalist databanks are not HLA-specific, but rather large
international data repositories for all organisms. The three main gen-
eral nucleotide sequence databases are the EMBL (1), GenBank (2),
and the DDBJ (3). These three databases form an international col-
laboration and exchange sequences daily, so that each contains iden-
tical data. Most published sequences can be found in these
databases. The retrieval of HLA sequences from these systems is
possible through a number of tools. The EMBL database will be
used as the model system for all examples in this chapter.
A number of different methods can be used to retrieve HLA
sequences. A conceptually simple approach would be to copy the
entire database to the users system and then to remove all nonrel-
evant entries leaving a smaller HLA-related database. However, this
method would actually take longer than most search tools, as only a
small subset (around 0.001%) of the database represents HLA data.
A more pragmatic approach is to use the search tools provided,
although these may be time-consuming if large numbers of
sequences are being retrieved. Search tools allow you to perform
complex queries and download the retrieved entries in a specified
HLA Informatics 5
format. The search engines for EMBL are maintained by the Euro-
pean Bioinformatics Institute (EBI). The search engines are also
mirrored at other sites on the Internet, allowing the user to access a
local server. The EMBL database is very large database containing
over 17 million nucleotide sequences, and to this are linked other
databases like SWISS-PROT and TREMBL (translations of EMBL)
(4). All these databases are available and can be searched at the EBI
Web site. In this chapter, we will only discuss the retrieval of nucle-
otide sequences, although the same methods apply for the retrieval
of protein sequences from the appropriate database.
The EMBL database receives around 14,000 sequences/12
megabases of sequence per day, and this data is processed and made
available through flat files. These files include sequence features,
which provide a large amount of additional data allowing for ad-
vanced queries. Sequence features are best described as a number of
different motifs, references and data particular to the DNA se-
quence. The most common sequence features are the source of se-
quence (species, cell type, etc.), coding details, exon coordinates,
and protein translation. Additional sequence features include pro-
moter sequences and their coordinates and complimentary se-
quences. There are two main approaches for sequence searching.
One is to search on particular keywords or features contained within
the sequence documentation, and the other is to search for the actual
nucleotide or protein sequence.
2.2. Sequence Similarity Searches
Sequence similarity searches look for matches to the actual
sequence from larger databases. These matches are based on a num-
ber of similarity measures and, in general, retrieve identical or
highly similar sequences. The most recognized sequence similarity
search tool is the Basic Local Alignment Search Tool (BLAST)
algorithm (5). This widely distributed algorithm has been refined
over many years (6) and is now the premier sequence similarity
search tool. There are number of tools within the BLAST family,
BLASTN for nucleotides, BLASTP for proteins, and BLASTX for
6 Robinson and Marsh
translated sequences. BLAST works by searching for areas of local
similarity between sequences (see Fig. 1). These regions are then
linked to form a score for a particular sequence. The higher the
score, the more accurate the match. The BLAST algorithm does
suffer from a particular problem when using it to identify some HLA
sequences. The first general problem with BLAST is that very short
sequences cannot be used, the minimum sequence length is 20 bps.
The second problem associated with HLA sequences is due to the
high similarity between HLA alleles. BLAST can accurately
retrieve HLA entries from a database where there are a huge range
of sequences, i.e., EMBL. However, when used on a more specialist
subset of data, care is needed when analyzing the results. BLAST
has its own scoring system and uses this rather than sequence iden-
tity. In this system, a 546-bp sequence of approx 95% identity may
score higher than a shorter (e.g., 270 bps) sequence of 100% iden-
tity. Users should therefore study the large output files carefully, as
identical matches may not appear first in the output.
2.3. Sequence Search Tools
The EBI provides one of the most advanced flat file search tools,
the Sequence Retrieval System (SRS) (7). This tool allows the user
to search on any of the sequence features, accession numbers, key-
words, or sequence description and is probably the best method of
retrieving HLA sequences from a general nucleotide database. The
disadvantage of the SRS system is that it does require some famil-
iarity with the flat file format (see Fig. 2). Once users are accus-
tomed to the way data is presented, they can quickly build up very
complex queries. An advantage of the SRS tool is that it can also be
Fig. 1. (opposite page) SRS search tool showing flat file output. The
figure shows the standard output of a flat file, which is a text-based file
that identifies different sections by the line headings, e.g., AC, accession
number; DE, description; KW, keywords; DR, cross references to other
databases; and SQ, sequence. Lines also begin with O, phylogeny;
R, references; and F, features. The output file shown is taken from the
EMBL Nucleotide Sequence Database.
HLA Informatics 7
8 Robinson and Marsh
HLA Informatics 9
used to launch other applications, e.g., BLAST. The SRS tool also
allows the users to customize the output of searches, meaning that
you can quickly see how relevant entries are to the search criteria.
SRS can be found at the EBI Web site and can be used to search a
number of different databases.
The GenBank search engine, Entrez (8) also works on accession
numbers, but provides several advanced options. These include bulk
retrievals of entries in a preformatted manner. This is very useful
for retrieving sequences, once a list of known accession numbers is
available. The search engine for DDBJ is restricted to searching via
accession numbers.
2.4. Other Generalist Sequence Databases
There are other databases that are not included in the EMBL/
GenBank/DDBJ collaboration. These systems also have their own
search engines and retrieval facilities, and similar problems with
regard to data integrity and sequence retrieval also apply, which
will be discussed later (see Subheading 2.5.).
The Genome Sequence DataBase (GSDB) (9) is run by the National
Center for Genome Resources, USA. The GSDB database is included
here, as there are a number of HLA sequences unique to this database
and GSDB does not automatically forward these to the other main
databases. The GSDB search engine retrieves entries and sequence
features, but only by accession number. This means that an accession
number must be known before a sequence can be retrieved.
Fig. 2. (opposite page) Example BLAST outputs. Selected sections of
a standard BLAST output for a search using the A*01011 sequence
against the EMBL database. The first part of the figure shows the
sequences and descriptions retrieved by the EMBL accession numbers.
The variation in Keywords and Description can be seen here; also note
the lack of official nomenclature. Please note inclusion of Pygmy Chim-
panzee (Pan paniscus) sequence which is high in the scoring due to their
high sequence similarity. The second part of this figure shows how
BLAST displays the sequence identities. Identity is shown by a pipe (|)
between the bases, and mismatches have no join.
